Robust state estimation for discrete-time genetic regulatory networks with randomly occurring uncertainties

摘要: In this paper, we investigate the problem of robust state estimator design for a class uncertain discrete-time genetic regulatory networks (GRNs) with time varying delays and randomly occurring uncertainties. By introducing new discretized Lyapunov–Krasovskii functional together free-weighting matrix technique, first derive set sufficient conditions existence global asymptotic GRN model satisfying both lower upper bound interval time-varying delay. Further, obtained results are extended to deal in presence uncertainties which obey certain mutually uncorrelated Bernoulli distributed white noise sequences. The proposed criterions established terms linear inequalities (LMIs) can be easily solved via Matlab LMI toolbox. Finally, has been implemented gene network illustrate applicability usefulness theory.